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For example: a marketplace simulation requires, by its very nature, a high degree of interconnection between entities that are carrying out different parts of calculation. Many, (if not most), real-world tasks simply cannot be broken down as easily as SETI calculation.
So how does Oracle, a database company, justify calling its latest database 10g (where g stands for Grid)? Why does Sun believe that its business customers will benefit from Grid technologies?
In case of Oracle, they are just referring to a technology that has been around for a while called clustering. Clustering simply connects several computers together to act as one. This is nothing new and Grid in this context is nothing more than hype - Oracle are just using a topical 'buzzword' to market an already-existing technology.
Sun, on other hand, may have a more reasonable position. It touts intra-company Grids rather than ones based on a worldwide reach. In these cases, above analysis breaks down - as cost of network transmission inside a company is a tiny fraction of that over Internet. However, there are still only a small number of applications that could benefit from such a configuration.
That said; there are a few notable exceptions. Smaller architecture firms, which lack huge computing resources required to ensure safety of more ambitious projects, will be able to have their designs tested using Grid computing power: input (a technical drawing) and output (a structural analysis) are tiny compared to massive amount of processing that needs to be done.
Similarly, 3D animation studios could render movies using Grid; as 3D model input and picture that is output are again small compared to processing required.
This article is not to say that computing Grids won't have an impact on our lives - high end scientific projects such as cancer research, human genome research and development of new materials will benefit hugely from huge pool of computing resource that Grid promises.
In commercial world however, Grid will only impact very largest of enterprises until network connectivity is as cheap and readily available as processing power. With Moore's Law2 still holding, that is not likely to happen any time soon.
To summarise then, computing nirvana of processing and storage on demand (also known as utility computing) is a long way off - both technically and, most importantly, economically.
If you would like any more information, please contact FWOSS - we'll be happy to discuss our views with you.
1 Distributed Computing Economics Jim Gray March 2003 2 "Processor speed will double every 18 months."
This article is copyright Fire Without Smoke Software Ltd 2003. FWOSS can be contacted at www.fwoss.com Please feel free to reproduce this article on your site with appropriate credits.
Thom is FWOSS' operations director